from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HpMatchReporting(other_library="sklearnex", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 0.048 | 100000 | 1000 | 100 | 2.021145 | 0.040212 | NaN | 0.000396 | 0.002021 | brute | -1 | 1 | 0.629 | 0.409500 | 0.010805 | 0.677 | 4.935642 | 4.937360 |
| 2 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.027088 | 0.002983 | NaN | 0.000030 | 0.027088 | brute | -1 | 1 | 0.000 | 0.010904 | 0.000302 | 1.000 | 2.484203 | 2.485158 |
| 4 | KNeighborsClassifier_brute_force | predict | 0.011 | 100000 | 1000 | 100 | 2.993528 | 0.037443 | NaN | 0.000267 | 0.002994 | brute | -1 | 5 | 0.688 | 0.405776 | 0.008452 | 0.677 | 7.377297 | 7.378897 |
| 5 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.027682 | 0.003318 | NaN | 0.000029 | 0.027682 | brute | -1 | 5 | 0.000 | 0.011016 | 0.000442 | 1.000 | 2.512927 | 2.514946 |
| 7 | KNeighborsClassifier_brute_force | predict | 0.063 | 100000 | 1000 | 100 | 2.372928 | 0.019051 | NaN | 0.000337 | 0.002373 | brute | 1 | 100 | 0.797 | 0.410192 | 0.007477 | 0.734 | 5.784922 | 5.785883 |
| 8 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.022579 | 0.001141 | NaN | 0.000035 | 0.022579 | brute | 1 | 100 | 0.000 | 0.011469 | 0.000371 | 1.000 | 1.968671 | 1.969700 |
| 10 | KNeighborsClassifier_brute_force | predict | 0.008 | 100000 | 1000 | 100 | 3.005309 | 0.038994 | NaN | 0.000266 | 0.003005 | brute | -1 | 100 | 0.797 | 0.457185 | 0.006563 | 0.805 | 6.573508 | 6.574186 |
| 11 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.027082 | 0.002393 | NaN | 0.000030 | 0.027082 | brute | -1 | 100 | 0.000 | 0.010991 | 0.000461 | 1.000 | 2.463966 | 2.466131 |
| 13 | KNeighborsClassifier_brute_force | predict | 0.046 | 100000 | 1000 | 100 | 2.371938 | 0.016693 | NaN | 0.000337 | 0.002372 | brute | 1 | 5 | 0.688 | 0.403940 | 0.002088 | 0.734 | 5.872005 | 5.872084 |
| 14 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.023610 | 0.001646 | NaN | 0.000034 | 0.023610 | brute | 1 | 5 | 0.000 | 0.011638 | 0.001254 | 1.000 | 2.028690 | 2.040440 |
| 16 | KNeighborsClassifier_brute_force | predict | 0.176 | 100000 | 1000 | 100 | 1.402930 | 0.008560 | NaN | 0.000570 | 0.001403 | brute | 1 | 1 | 0.629 | 0.453800 | 0.009094 | 0.805 | 3.091512 | 3.092133 |
| 17 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.022103 | 0.000962 | NaN | 0.000036 | 0.022103 | brute | 1 | 1 | 0.000 | 0.010854 | 0.000373 | 1.000 | 2.036351 | 2.037551 |
| 19 | KNeighborsClassifier_brute_force | predict | 0.019 | 100000 | 1000 | 2 | 1.726828 | 0.024760 | NaN | 0.000009 | 0.001727 | brute | -1 | 1 | 0.951 | 0.085150 | 0.002206 | 0.970 | 20.279723 | 20.286526 |
| 22 | KNeighborsClassifier_brute_force | predict | 0.001 | 100000 | 1000 | 2 | 2.755071 | 0.023094 | NaN | 0.000006 | 0.002755 | brute | -1 | 5 | 0.971 | 0.085879 | 0.003378 | 0.970 | 32.080801 | 32.105605 |
| 25 | KNeighborsClassifier_brute_force | predict | 0.009 | 100000 | 1000 | 2 | 2.214361 | 0.009550 | NaN | 0.000007 | 0.002214 | brute | 1 | 100 | 0.969 | 0.085842 | 0.001648 | 0.978 | 25.795911 | 25.800662 |
| 28 | KNeighborsClassifier_brute_force | predict | 0.006 | 100000 | 1000 | 2 | 2.777270 | 0.022325 | NaN | 0.000006 | 0.002777 | brute | -1 | 100 | 0.969 | 0.139361 | 0.004774 | 0.975 | 19.928533 | 19.940225 |
| 31 | KNeighborsClassifier_brute_force | predict | 0.007 | 100000 | 1000 | 2 | 2.205840 | 0.012963 | NaN | 0.000007 | 0.002206 | brute | 1 | 5 | 0.971 | 0.086497 | 0.002374 | 0.978 | 25.501951 | 25.511556 |
| 34 | KNeighborsClassifier_brute_force | predict | 0.024 | 100000 | 1000 | 2 | 1.171084 | 0.005302 | NaN | 0.000014 | 0.001171 | brute | 1 | 1 | 0.951 | 0.136675 | 0.003830 | 0.975 | 8.568405 | 8.571768 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.001 | 6.204 | 0.0 | -1 | 1 | 0.051 | 0.002 | 0.252 | 0.252 | ||
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.001 | 6.300 | 0.0 | -1 | 5 | 0.052 | 0.001 | 0.242 | 0.242 | ||
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.002 | 5.884 | 0.0 | 1 | 100 | 0.051 | 0.000 | 0.266 | 0.266 | ||
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.000 | 6.396 | 0.0 | -1 | 100 | 0.054 | 0.001 | 0.233 | 0.233 | ||
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.000 | 6.351 | 0.0 | 1 | 5 | 0.052 | 0.002 | 0.242 | 0.243 | ||
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.000 | 6.226 | 0.0 | 1 | 1 | 0.053 | 0.002 | 0.240 | 0.241 | ||
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.316 | 0.0 | -1 | 1 | 0.009 | 0.001 | 0.552 | 0.553 | ||
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.325 | 0.0 | -1 | 5 | 0.009 | 0.000 | 0.534 | 0.534 | ||
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.320 | 0.0 | 1 | 100 | 0.010 | 0.002 | 0.513 | 0.520 | ||
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.324 | 0.0 | -1 | 100 | 0.009 | 0.000 | 0.538 | 0.538 | ||
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.006 | 0.001 | 0.288 | 0.0 | 1 | 5 | 0.009 | 0.000 | 0.648 | 0.649 | ||
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.001 | 0.315 | 0.0 | 1 | 1 | 0.009 | 0.000 | 0.565 | 0.566 |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.021 | 0.040 | 0.000 | 0.002 | -1 | 1 | 0.409 | 0.011 | 4.936 | 4.937 | ||
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.027 | 0.003 | 0.000 | 0.027 | -1 | 1 | 0.011 | 0.000 | 2.484 | 2.485 | ||
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.994 | 0.037 | 0.000 | 0.003 | -1 | 5 | 0.406 | 0.008 | 7.377 | 7.379 | ||
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.028 | 0.003 | 0.000 | 0.028 | -1 | 5 | 0.011 | 0.000 | 2.513 | 2.515 | ||
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.373 | 0.019 | 0.000 | 0.002 | 1 | 100 | 0.410 | 0.007 | 5.785 | 5.786 | ||
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | 0.000 | 0.023 | 1 | 100 | 0.011 | 0.000 | 1.969 | 1.970 | ||
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.005 | 0.039 | 0.000 | 0.003 | -1 | 100 | 0.457 | 0.007 | 6.574 | 6.574 | ||
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.027 | 0.002 | 0.000 | 0.027 | -1 | 100 | 0.011 | 0.000 | 2.464 | 2.466 | ||
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.372 | 0.017 | 0.000 | 0.002 | 1 | 5 | 0.404 | 0.002 | 5.872 | 5.872 | ||
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.024 | 0.002 | 0.000 | 0.024 | 1 | 5 | 0.012 | 0.001 | 2.029 | 2.040 | ||
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.403 | 0.009 | 0.001 | 0.001 | 1 | 1 | 0.454 | 0.009 | 3.092 | 3.092 | ||
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.001 | 0.000 | 0.022 | 1 | 1 | 0.011 | 0.000 | 2.036 | 2.038 | ||
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.727 | 0.025 | 0.000 | 0.002 | -1 | 1 | 0.085 | 0.002 | 20.280 | 20.287 | ||
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.011 | 0.006 | 0.000 | 0.011 | -1 | 1 | 0.001 | 0.000 | 19.016 | 19.348 | ||
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.755 | 0.023 | 0.000 | 0.003 | -1 | 5 | 0.086 | 0.003 | 32.081 | 32.106 | ||
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.008 | 0.002 | 0.000 | 0.008 | -1 | 5 | 0.001 | 0.000 | 12.701 | 12.951 | ||
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.214 | 0.010 | 0.000 | 0.002 | 1 | 100 | 0.086 | 0.002 | 25.796 | 25.801 | ||
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 5.241 | 5.324 | ||
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.777 | 0.022 | 0.000 | 0.003 | -1 | 100 | 0.139 | 0.005 | 19.929 | 19.940 | ||
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.010 | 0.002 | 0.000 | 0.010 | -1 | 100 | 0.001 | 0.000 | 15.222 | 15.424 | ||
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.206 | 0.013 | 0.000 | 0.002 | 1 | 5 | 0.086 | 0.002 | 25.502 | 25.512 | ||
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 5 | 0.001 | 0.000 | 5.157 | 5.231 | ||
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.171 | 0.005 | 0.000 | 0.001 | 1 | 1 | 0.137 | 0.004 | 8.568 | 8.572 | ||
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 0.001 | 0.000 | 2.980 | 3.020 |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 0.009 | 1000000 | 1000 | 10 | 3.664288 | 0.021723 | NaN | 0.000022 | 0.003664 | kd_tree | -1 | 100 | 0.907 | 0.140077 | 0.006822 | 0.898 | 26.159020 | 26.190022 |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.009 | 1000000 | 1000 | 10 | 6.279532 | 0.022999 | NaN | 0.000013 | 0.006280 | kd_tree | 1 | 100 | 0.907 | 0.137837 | 0.002814 | 0.898 | 45.557605 | 45.567095 |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.062 | 1000000 | 1000 | 10 | 1.038654 | 0.015005 | NaN | 0.000077 | 0.001039 | kd_tree | 1 | 1 | 0.868 | 0.721264 | 0.009439 | 0.930 | 1.440048 | 1.440171 |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.019 | 1000000 | 1000 | 10 | 1.149265 | 0.013332 | NaN | 0.000070 | 0.001149 | kd_tree | -1 | 5 | 0.912 | 0.247547 | 0.004057 | 0.931 | 4.642610 | 4.643233 |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.063 | 1000000 | 1000 | 10 | 0.614735 | 0.005860 | NaN | 0.000130 | 0.000615 | kd_tree | -1 | 1 | 0.868 | 0.248266 | 0.003278 | 0.931 | 2.476113 | 2.476329 |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.018 | 1000000 | 1000 | 10 | 1.982398 | 0.011555 | NaN | 0.000040 | 0.001982 | kd_tree | 1 | 5 | 0.912 | 0.737868 | 0.015006 | 0.930 | 2.686656 | 2.687212 |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.041 | 1000 | 1000 | 2 | 0.050027 | 0.009165 | NaN | 0.000320 | 0.000050 | kd_tree | -1 | 100 | 0.910 | 0.000580 | 0.000095 | 0.951 | 86.247184 | 87.402205 |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.041 | 1000 | 1000 | 2 | 0.042774 | 0.001215 | NaN | 0.000374 | 0.000043 | kd_tree | 1 | 100 | 0.910 | 0.000566 | 0.000113 | 0.951 | 75.541148 | 77.020639 |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.044 | 1000 | 1000 | 2 | 0.028988 | 0.000969 | NaN | 0.000552 | 0.000029 | kd_tree | 1 | 1 | 0.948 | 0.005078 | 0.001437 | 0.904 | 5.708113 | 5.932131 |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.009 | 1000 | 1000 | 2 | 0.035712 | 0.003421 | NaN | 0.000448 | 0.000036 | kd_tree | -1 | 5 | 0.958 | 0.000877 | 0.000177 | 0.949 | 40.725710 | 41.545230 |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 1000 | 1000 | 2 | 0.032502 | 0.001419 | NaN | 0.000492 | 0.000033 | kd_tree | -1 | 1 | 0.948 | 0.000825 | 0.000112 | 0.949 | 39.373041 | 39.735831 |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.054 | 1000 | 1000 | 2 | 0.031148 | 0.001660 | NaN | 0.000514 | 0.000031 | kd_tree | 1 | 5 | 0.958 | 0.004434 | 0.000252 | 0.904 | 7.025005 | 7.036332 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2.961 | 0.031 | 0.027 | 0.0 | -1 | 100 | 0.795 | 0.018 | 3.726 | 3.727 | ||
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.671 | 0.035 | 0.017 | 0.0 | 1 | 100 | 0.780 | 0.018 | 5.988 | 5.989 | ||
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.691 | 0.051 | 0.017 | 0.0 | 1 | 1 | 0.788 | 0.014 | 5.952 | 5.953 | ||
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.718 | 0.066 | 0.017 | 0.0 | -1 | 5 | 0.737 | 0.014 | 6.404 | 6.405 | ||
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.731 | 0.031 | 0.017 | 0.0 | -1 | 1 | 0.777 | 0.017 | 6.093 | 6.094 | ||
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.730 | 0.048 | 0.017 | 0.0 | 1 | 5 | 0.749 | 0.018 | 6.312 | 6.314 | ||
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.021 | 0.0 | -1 | 100 | 0.004 | 0.002 | 0.213 | 0.237 | ||
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.024 | 0.0 | 1 | 100 | 0.004 | 0.003 | 0.164 | 0.202 | ||
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.024 | 0.0 | 1 | 1 | 0.001 | 0.000 | 0.629 | 0.639 | ||
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.023 | 0.0 | -1 | 5 | 0.001 | 0.000 | 0.682 | 0.685 | ||
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.023 | 0.0 | -1 | 1 | 0.001 | 0.000 | 0.692 | 0.696 | ||
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.023 | 0.0 | 1 | 5 | 0.001 | 0.000 | 0.662 | 0.669 |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.664 | 0.022 | 0.000 | 0.004 | -1 | 100 | 0.140 | 0.007 | 26.159 | 26.190 | ||
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.011 | 0.001 | 0.000 | 0.011 | -1 | 100 | 0.001 | 0.000 | 17.632 | 18.646 | ||
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 6.280 | 0.023 | 0.000 | 0.006 | 1 | 100 | 0.138 | 0.003 | 45.558 | 45.567 | ||
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.007 | 0.001 | 0.000 | 0.007 | 1 | 100 | 0.001 | 0.000 | 12.177 | 13.095 | ||
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.039 | 0.015 | 0.000 | 0.001 | 1 | 1 | 0.721 | 0.009 | 1.440 | 1.440 | ||
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.001 | 0.000 | 0.002 | 1 | 1 | 0.002 | 0.000 | 0.980 | 1.011 | ||
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.149 | 0.013 | 0.000 | 0.001 | -1 | 5 | 0.248 | 0.004 | 4.643 | 4.643 | ||
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 5 | 0.001 | 0.000 | 6.273 | 6.610 | ||
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.615 | 0.006 | 0.000 | 0.001 | -1 | 1 | 0.248 | 0.003 | 2.476 | 2.476 | ||
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.000 | 0.000 | 0.004 | -1 | 1 | 0.001 | 0.000 | 5.364 | 5.662 | ||
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.982 | 0.012 | 0.000 | 0.002 | 1 | 5 | 0.738 | 0.015 | 2.687 | 2.687 | ||
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.001 | 0.000 | 0.002 | 1 | 5 | 0.002 | 0.001 | 1.415 | 1.484 | ||
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.050 | 0.009 | 0.000 | 0.000 | -1 | 100 | 0.001 | 0.000 | 86.247 | 87.402 | ||
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 100 | 0.000 | 0.000 | 18.175 | 19.762 | ||
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.043 | 0.001 | 0.000 | 0.000 | 1 | 100 | 0.001 | 0.000 | 75.541 | 77.021 | ||
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 0.000 | 0.000 | 4.087 | 4.895 | ||
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.029 | 0.001 | 0.001 | 0.000 | 1 | 1 | 0.005 | 0.001 | 5.708 | 5.932 | ||
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 4.565 | 5.252 | ||
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.036 | 0.003 | 0.000 | 0.000 | -1 | 5 | 0.001 | 0.000 | 40.726 | 41.545 | ||
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 5 | 0.000 | 0.000 | 17.236 | 19.242 | ||
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.033 | 0.001 | 0.000 | 0.000 | -1 | 1 | 0.001 | 0.000 | 39.373 | 39.736 | ||
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 15.979 | 17.362 | ||
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.031 | 0.002 | 0.001 | 0.000 | 1 | 5 | 0.004 | 0.000 | 7.025 | 7.036 | ||
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 4.967 | 5.383 |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.664 | 0.016 | 30 | 0.024 | 0.0 | k-means++ | 0.289 | 0.005 | 2.299 | 2.299 | ||
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.557 | 0.007 | 30 | 0.029 | 0.0 | random | 0.334 | 0.014 | 1.667 | 1.668 | ||
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 7.069 | 0.049 | 30 | 0.113 | 0.0 | k-means++ | 3.777 | 0.031 | 1.872 | 1.872 | ||
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.572 | 0.042 | 30 | 0.122 | 0.0 | random | 3.977 | 0.020 | 1.652 | 1.652 |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.0 | 30 | 0.009 | 0.000 | k-means++ | 0.0 | 0.0 | 7.471 | 7.820 | ||
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.0 | 30 | 0.000 | 0.002 | k-means++ | 0.0 | 0.0 | 9.510 | 10.174 | ||
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.0 | 30 | 0.009 | 0.000 | random | 0.0 | 0.0 | 7.478 | 7.983 | ||
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.0 | 30 | 0.000 | 0.002 | random | 0.0 | 0.0 | 10.266 | 11.132 | ||
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.0 | 30 | 0.386 | 0.000 | k-means++ | 0.0 | 0.0 | 5.840 | 7.115 | ||
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.0 | 30 | 0.000 | 0.002 | k-means++ | 0.0 | 0.0 | 8.749 | 9.470 | ||
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.0 | 30 | 0.389 | 0.000 | random | 0.0 | 0.0 | 6.537 | 6.913 | ||
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.0 | 30 | 0.000 | 0.002 | random | 0.0 | 0.0 | 8.691 | 9.339 |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | diff_adjusted_rand_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | init | max_iter | n_clusters | n_init | tol | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4 | KMeans_short | predict | 0.004085 | 10000 | 1000 | 2 | 0.002223 | 0.000336 | 20 | 0.007196 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.003724 | 0.000670 | 0.000212 | -0.000361 | 3.317051 | 3.478682 |
| 7 | KMeans_short | predict | 0.019341 | 10000 | 1000 | 100 | 0.003351 | 0.000309 | 20 | 0.238743 | 0.000003 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.348183 | 0.001483 | 0.000182 | 0.328841 | 2.258812 | 2.275814 |
| 10 | KMeans_short | predict | 0.015990 | 10000 | 1000 | 100 | 0.003308 | 0.000295 | 20 | 0.241874 | 0.000003 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.303254 | 0.001558 | 0.000258 | 0.287264 | 2.123517 | 2.152343 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.095 | 0.006 | 20 | 0.002 | 0.0 | random | 0.049 | 0.001 | 1.949 | 1.949 | ||
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.294 | 0.004 | 20 | 0.001 | 0.0 | k-means++ | 0.131 | 0.006 | 2.234 | 2.236 | ||
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.318 | 0.005 | 20 | 0.025 | 0.0 | random | 0.251 | 0.004 | 1.270 | 1.270 | ||
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 1.081 | 0.019 | 20 | 0.007 | 0.0 | k-means++ | 0.600 | 0.006 | 1.803 | 1.803 |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.008 | 0.000 | random | 0.001 | 0.000 | 3.050 | 3.126 | ||
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | random | 0.000 | 0.000 | 8.627 | 9.882 | ||
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.007 | 0.000 | k-means++ | 0.001 | 0.000 | 3.317 | 3.479 | ||
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | k-means++ | 0.000 | 0.000 | 9.097 | 9.687 | ||
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.000 | 20 | 0.239 | 0.000 | random | 0.001 | 0.000 | 2.259 | 2.276 | ||
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.003 | 0.003 | 20 | 0.000 | 0.003 | random | 0.001 | 0.002 | 3.854 | 8.939 | ||
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.000 | 20 | 0.242 | 0.000 | k-means++ | 0.002 | 0.000 | 2.124 | 2.152 | ||
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | k-means++ | 0.000 | 0.000 | 8.704 | 9.285 |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 0.006 | 1000000 | 1000 | 100 | 0.000354 | 0.000095 | [17] | 2.260383 | 3.539223e-07 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.611 | 0.000400 | 0.000099 | 0.605 | 0.883737 | 0.910129 |
| 2 | LogisticRegression | predict | 1.000 | 1000000 | 1 | 100 | 0.000094 | 0.000048 | [17] | 0.008556 | 9.350320e-05 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.000 | 0.000251 | 0.000088 | 1.000 | 0.372970 | 0.395276 |
| 4 | LogisticRegression | predict | 0.040 | 1000 | 100 | 10000 | 0.002309 | 0.000156 | [26] | 3.465245 | 2.308639e-05 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.280 | 0.004128 | 0.000287 | 0.240 | 0.559228 | 0.560579 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 15.048 | 0.111 | [17] | 0.053 | 0.000 | 2.698 | 0.008 | 5.577 | 5.577 | ||
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 1.236 | 0.031 | [26] | 0.065 | 0.001 | 1.070 | 0.030 | 1.155 | 1.156 |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | [17] | 2.260 | 0.0 | 0.000 | 0.0 | 0.884 | 0.910 | ||
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | [17] | 0.009 | 0.0 | 0.000 | 0.0 | 0.373 | 0.395 | ||
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.0 | [26] | 3.465 | 0.0 | 0.004 | 0.0 | 0.559 | 0.561 | ||
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | [26] | 0.631 | 0.0 | 0.001 | 0.0 | 0.133 | 0.138 |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | diff_r2_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | r2_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | r2_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 0.010925 | 1000 | 1000 | 10000 | 0.01204 | 0.000956 | NaN | 6.644538 | 0.000012 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 0.086907 | 0.019506 | 0.001049 | 0.097831 | 0.617246 | 0.618137 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.271 | 0.006 | 0.296 | 0.0 | 0.300 | 0.005 | 0.904 | 0.904 | ||
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.252 | 0.052 | 0.639 | 0.0 | 0.341 | 0.004 | 3.669 | 3.669 |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.012 | 0.001 | 6.645 | 0.0 | 0.02 | 0.001 | 0.617 | 0.618 | ||
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.000 | 0.000 | 0.774 | 0.0 | 0.00 | 0.000 | 0.643 | 0.694 | ||
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.000 | 0.000 | 4.493 | 0.0 | 0.00 | 0.000 | 0.667 | 0.702 | ||
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.000 | 0.000 | 0.009 | 0.0 | 0.00 | 0.000 | 0.601 | 0.659 |